def generate_all_measurements_and_simulation_log_13():
"""Generate the files ALL_MEAS_13, MEASUREMENTS_13, and HEADER_13.
Note that data for ALL_MEAS_13 comes from the time series database,
while MEASUREMENTS_13 and HEADER_13 come straight from the platform.
"""
# Define a helper for writing our measurements and headers to file.
def meas_header_to_file(header, message):
_dict_to_json(data=header, fname=HEADER_13)
_dict_to_json(data=message, fname=MEASUREMENTS_13)
# Initialize list for placing the simulation logs.
logs = []
# Define helper function for collecting our log messages.
def add_log_entry(header, message):
logs.append({'header': header, 'message': message})
# Get a platform manager, start the simulation.
platform = gridappsd_platform.PlatformManager()
# For now, we need a 2nd platform manager since it seems subscribing
# to the simulation logs interferes with the Simulation object under
# the hood.
platform2 = gridappsd_platform.PlatformManager()
sim_id = platform.run_simulation(feeder_id=FEEDER_MRID_13,
start_time=MEAS_13_START,
duration=MEAS_13_DURATION,
realtime=False)
# Subscribe to simulation logs.
platform2.gad.subscribe(topic=topics.simulation_log_topic(sim_id),
callback=add_log_entry)
# Subscribe to simulation output so we can write the header +
# message to file. Note this is not particularly efficient as the
# files will be overwritten a few times before the simulation ends.
# Who cares? Not me :) Just gotta make rapid progress.
platform.gad.subscribe(topic=topics.simulation_output_topic(sim_id),
callback=meas_header_to_file)
# Wait for simulation completion.
platform.wait_for_simulation()
# Get the measurements.
# noinspection PyProtectedMember
data = platform._query_simulation_output(simulation_id=sim_id)
# Write to file.
_dict_to_json(fname=ALL_MEAS_13, data=data)
_dict_to_json(data=logs, fname=SIMULATION_LOG)
def generate_energy_consumer_measurements_9500():
"""Generate energy_consumer_measurements_9500.json"""
platform = gridappsd_platform.PlatformManager()
starttime = datetime(2013, 1, 14, 0, 0)
sim_id = platform.run_simulation(feeder_id=FEEDER_MRID_9500,
start_time=starttime,
duration=20,
realtime=False)
# Get load measurement data. Save time by reading the csv.
load_meas = pd.read_csv(LOAD_MEAS_9500)
# Extract the first entry.
mrid = load_meas.iloc[0]['id']
# Wait for simulation completion.
platform.wait_for_simulation()
# TODO: Remove this time.sleep when
# https://github.com/GRIDAPPSD/gridappsd-forum/issues/24#issue-487936782
# has been addressed.
time.sleep(10)
# Get the measurements.
# noinspection PyProtectedMember
data = platform._query_simulation_output(simulation_id=sim_id,
measurement_mrid=mrid)
# Write to file.
_dict_to_json(fname=E_CONS_MEAS_9500, data=data)
def generate_weather_simple():
"""Generate simple single-entry weather data."""
p = gridappsd_platform.PlatformManager()
# Start with the json file.
# noinspection PyProtectedMember
j = p._query_weather(start_time=WEATHER_SIMPLE_START,
end_time=WEATHER_SIMPLE_END)
_dict_to_json(j, WEATHER_SIMPLE_JSON)
def generate_weather_two_week():
"""Generate two weeks worth of data in 15 minute intervals."""
p = gridappsd_platform.PlatformManager()
d = p.get_weather(start_time=WEATHER_TWO_WEEK_START,
end_time=WEATHER_TWO_WEEK_END)
to_file(d.resample('15Min', closed='right', label='right').mean(),
WEATHER_TWO_WEEK,
index=True)
def generate_model_info():
"""Generate 'query_model_info.json.
"""
platform = gridappsd_platform.PlatformManager()
info = platform.gad.query_model_info()
_dict_to_json(data=info, fname=MODEL_INFO)
def test_send_command_no_sim_id(self):
"""Ensure things properly blow up if there's no simulation ID to
be found when trying to send a command.
"""
# Get a fresh manager.
p = gridappsd_platform.PlatformManager()
with self.assertRaisesRegex(ValueError, 'In order to send a command,'):
p.send_command(object_ids=['a'], attributes=['b'],
forward_values=[1], reverse_values=[2])
def generate_weather_for_sensor_data_9500():
"""Get weather data that lines up with the sensor data.
"""
p = gridappsd_platform.PlatformManager()
# Start with the json file.
# noinspection PyProtectedMember
j = p._query_weather(start_time=SENSOR_MEASUREMENT_TIME_START,
end_time=SENSOR_MEASUREMENT_TIME_END)
_dict_to_json(j, WEATHER_FOR_SENSOR_DATA_9500_JSON)
d = p.get_weather(start_time=SENSOR_MEASUREMENT_TIME_START,
end_time=SENSOR_MEASUREMENT_TIME_END)
to_file(d, WEATHER_FOR_SENSOR_DATA_9500)
def test_run_simulation_actually_run(self):
"""Test run_simulation, and legitimately run a simulation. Note
this is more of an integration test, and also tests
_update_sim_complete and wait_for_simulation.
"""
# Get a fresh manager.
p = gridappsd_platform.PlatformManager()
# Use the smallest model we've got.
feeder_id = _df.FEEDER_MRID_13
# sim and sim_complete should be None.
self.assertIsNone(p.sim_complete)
self.assertIsNone(p.sim)
# Run the simulation.
p.run_simulation(feeder_id=feeder_id,
start_time=datetime(2013, 1, 1, 0, 0, 0),
duration=5, realtime=False, random_zip=False,
houses=False)
# While the simulation is still running, sim_complete should be
# False. NOTE: This builds in the assumption that this Python
# code will take less time than the platform does to generate
# and run the model. Seems reasonable.
self.assertFalse(p.sim_complete)
# sim should now be a gridappsd.simulation.Simulation object.
self.assertIsInstance(p.sim, simulation.Simulation)
# Wait for the simulation to complete.
with utils.time_limit(10):
p.wait_for_simulation()
# Now, sim_complete should be None.
self.assertIsNone(p.sim_complete)
# Dictionary of model MRIDs to file names. Note the 9500 node isn't
# truly from IEEE (it's a modified version of the 8500), but better to
# keep consistent + simple naming conventions.
MODELS = {
'_4F76A5F9-271D-9EB8-5E31-AA362D86F2C3': 'ieee_8500',
'_49AD8E07-3BF9-A4E2-CB8F-C3722F837B62': 'ieee_13',
'_C1C3E687-6FFD-C753-582B-632A27E28507': 'ieee_123',
'_AAE94E4A-2465-6F5E-37B1-3E72183A4E44': 'ieee_9500'
}
# For convenience, create constants which other testing modules can
# import.
IEEE_8500 = os.path.join(MODEL_DIR, 'ieee_8500.glm')
IEEE_13 = os.path.join(MODEL_DIR, 'ieee_13.glm')
IEEE_123 = os.path.join(MODEL_DIR, 'ieee_123.glm')
# Modified 123 provided by Yuan so I (Brandon) can update glm.py for
# him.
IEEE_123_mod = os.path.join(MODEL_DIR, 'ieee_123_mod.glm')
IEEE_9500 = os.path.join(MODEL_DIR, 'ieee_9500.glm')
if __name__ == '__main__':
platform = gridappsd_platform.PlatformManager()
for mrid, model in MODELS.items():
# Pull the model from the platform.
model_str = platform.get_glm(model_id=mrid)
with open(os.path.join(MODEL_DIR, model + '.glm'), 'w') as f:
f.write(model_str)
# That's it.
def generate_sensor_service_measurements_9500():
"""Use the sensor service to create average measurements for an
energy consumer, then extract the measurements from the timeseries
database and save them to file.
"""
time_diff = SENSOR_MEASUREMENT_TIME_END - SENSOR_MEASUREMENT_TIME_START
meas_data = _get_9500_meas_data_for_one_node()
# Create a configuration for running the sensor service so that
# we track the MRIDs of the given measurements.
sensor_config = {}
for mrid in meas_data['id']:
sensor_config[mrid] = {
# Well, this isn't true for all the measurements, but oh
# well. We care less about the values and more about
# actually getting the values.
"nominal-value": 120,
"perunit-confidence-band": 0.01,
# TODO: Is this in seconds or time steps?
"aggregation-interval": 30,
# No drop out for now.
"perunit-drop-rate": 0
}
full_config = [{
'id': "gridappsd-sensor-simulator",
'user_options': {
"sensors-config": sensor_config,
"random-seed": 42,
"default-aggregation-interval": 30,
"passthrough-if-not-specified": False,
"default-perunit-confidence-band": 0.01,
"default-perunit-drop-rate": 0
}
}]
platform = gridappsd_platform.PlatformManager()
# TODO: Use houses when
# https://github.com/GRIDAPPSD/gridappsd-forum/issues/26#issue-487939149
# is resolved.
sim_id = platform.run_simulation(feeder_id=FEEDER_MRID_9500,
start_time=SENSOR_MEASUREMENT_TIME_START,
duration=int(time_diff.total_seconds()),
realtime=False,
applications=[],
random_zip=False,
houses=False,
services=full_config,
events=None)
# Wait for simulation completion.
platform.wait_for_simulation()
# TODO: Remove this time.sleep when
# https://github.com/GRIDAPPSD/gridappsd-forum/issues/24#issue-487936782
# has been addressed.
time.sleep(30)
# Get output for all our MRIDs.
for idx, meas_mrid in enumerate(meas_data['id'].values):
# noinspection PyProtectedMember
out = platform._query_simulation_output(
simulation_id=sim_id,
measurement_mrid=meas_mrid,
query_measurement='gridappsd-sensor-simulator')
# Save the output to file.
_dict_to_json(data=out, fname=SENSOR_MEAS_LIST[idx])
# Now, generate a file which has all measurements in one place.
# NOTE: We'll ensure index_by_time is False.
out = platform.get_simulation_output(
simulation_id=sim_id,
query_measurement='gridappsd-sensor-simulator',
measurement_mrid=meas_data['id'].tolist(),
index_by_time=False)
# Save to file.
to_file(df=out, csv_file=PARSED_SENSOR_9500_ALL)
def generate_cap_reg_switch_inverter_machine_meas_message_9500():
"""Generate cap_meas_message_9500.json, reg_meas_message_9500.json,
switch_meas_message_9500.json, and inverter_meas_message_9500.json.
"""
# Load up the capacitor data.
caps = pd.read_csv(CAP_MEAS_9500)
cap_mrids = caps['state_meas_mrid'].tolist()
# Load up regulator data.
regs = pd.read_csv(REG_MEAS_9500)
reg_mrids = regs['pos_meas_mrid'].tolist()
# Load up switch data.
switches = pd.read_csv(SWITCH_MEAS_9500)
switch_mrids = switches['state_meas_mrid'].tolist()
# Load up inverter data.
inverters = pd.read_csv(INVERTER_MEAS_9500)
inverter_mrids = inverters['meas_mrid'].tolist()
# Load up synchronous machine data.
synch_mach = pd.read_csv(SYNCH_MACH_MEAS_9500)
machine_mrids = synch_mach['meas_mrid'].tolist()
# Initialize fn_mrid_list for a SimOutRouter.
fn_mrid_list = [{
'function': _dict_to_json,
'mrids': cap_mrids,
'kwargs': {
'fname': CAP_MEAS_MSG_9500
}
}, {
'function': _dict_to_json,
'mrids': reg_mrids,
'kwargs': {
'fname': REG_MEAS_MSG_9500
}
}, {
'function': _dict_to_json,
'mrids': switch_mrids,
'kwargs': {
'fname': SWITCH_MEAS_MSG_9500
}
}, {
'function': _dict_to_json,
'mrids': inverter_mrids,
'kwargs': {
'fname': INVERTER_MEAS_MSG_9500
}
}, {
'function': _dict_to_json,
'mrids': machine_mrids,
'kwargs': {
'fname': SYNCH_MACH_MEAS_MSG_9500
}
}]
platform = gridappsd_platform.PlatformManager()
starttime = datetime(2013, 1, 14, 16, 0)
sim_id = platform.run_simulation(feeder_id=FEEDER_MRID_9500,
start_time=starttime,
duration=5,
realtime=False)
# Create a SimOutRouter to save the measurements.
# noinspection PyUnusedLocal
router = gridappsd_platform.SimOutRouter(platform_manager=platform,
sim_id=sim_id,
fn_mrid_list=fn_mrid_list)
# Wait for simulation completion.
platform.wait_for_simulation()
def setUpClass(cls):
"""Get a PlatformManager."""
cls.platform = gridappsd_platform.PlatformManager()
